Experiments DB Dev
969c0205e8
Add make_variations.m + variation_analyze.m generating 20 self-contained subfolders under analysis/matlab/variations/, one per grouping x day-window, each with exactly three files: data.csv (curated subset), analyze.m (a simple standalone script fitting behavior ~ stim + day + stim:day + (1|rat) on the success COUNT), and result.txt (its output). Plus variations/SUMMARY.csv. Groupings (stim=1 / stim=0, other groups dropped): unmerge B2 vs A2 right_only B2+Right vs A2 (Box-A dropped) naive_a2 B2 vs A2+Naive (Right, Box-A dropped) naive_boxa B2 vs A2+Naive+Box-A (Right dropped) Windows: 0-10, 0-13, 0-5, 6-10, 6-13. All 20 have equal day coverage. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
66 lines
2.5 KiB
Plaintext
66 lines
2.5 KiB
Plaintext
==============================================================================
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VARIATION: right_only_d0_10
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==============================================================================
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model: behavior ~ stim + day + stim:day + (1|rat) (behavior = success COUNT)
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day = training day within window (0 = first analyzed day)
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treatment (stim=1): Electrode-Box-B2, Right-Electrode
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control (stim=0): Electrode-Box-A2
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N = 7 rats, 72 sessions raw day coverage: treat 0..10, control 0..10
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(equal day coverage over this window)
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==============================================================================
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FULL MODEL SUMMARY -- fitlme
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==============================================================================
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Linear mixed-effects model fit by ML
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Model information:
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Number of observations 72
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Fixed effects coefficients 4
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Random effects coefficients 7
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Covariance parameters 2
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Formula:
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behavior ~ 1 + day*stim + (1 | rat)
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Model fit statistics:
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AIC BIC LogLikelihood Deviance
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581.39 595.05 -284.69 569.39
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Fixed effects coefficients (95% CIs):
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Name Estimate SE tStat DF pValue
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{'(Intercept)'} 17.35 5.0416 3.4414 68 0.00099395
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{'day' } 7.979 0.75658 10.546 68 5.9429e-16
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{'stim' } 2.4226 6.6282 0.36549 68 0.71588
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{'day:stim' } 1.73 0.94724 1.8264 68 0.07218
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Lower Upper
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7.2897 27.411
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6.4693 9.4888
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-10.804 15.649
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-0.16015 3.6202
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Random effects covariance parameters (95% CIs):
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Group: rat (7 Levels)
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Name1 Name2 Type Estimate
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{'(Intercept)'} {'(Intercept)'} {'std'} 5.3461
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Lower Upper
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2.377 12.024
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Group: Error
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Name Estimate Lower Upper
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{'Res Std'} 11.956 10.063 14.205
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effect t (df) F (df1) p
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------------------------------------------------------------------
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stim x day (interaction) t(68)= 1.83 F(1)= 3.336 p=0.07218
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day (learning) t(68)= 10.55 F(1)= 111.222 p=5.943e-16
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stim (main, window start) t(68)= 0.37 F(1)= 0.134 p=0.7159
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interaction 95% CI: [-0.16, +3.62]
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INTERPRETATION: stim x day interaction n.s. -- slopes parallel (no differential learning rate) (p=0.07218, slope diff=+1.73)
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Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.
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